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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

CodeGPT
Freemium

BYOK AI coding assistant for VS Code and JetBrains with agentic coding and autocomplete using your own API keys from 15+ providers.

👁 262K/mo
Apify
✓ verifiedFreemium

Full-stack platform for web scraping, data extraction, and automation; category leader.

👁 4.4M/mo2.0K

Thin 'Lingbot-map' agent listing on github.com with zero traffic; too thin to tell.

5.2K
Pixels2Flutter
✓ verifiedFree

Turns UI screenshots into working Flutter code.

12K
Pricing
Free: $0
AutoComplete Add-on: $6.67/mo/seat (annual) or $8/mo/seat (monthly)
Free: $0/mo ($5 included usage)
Starter: $29/mo ($26/mo billed annually)
Scale: $199/mo ($179/mo billed annually)
Business: $999/mo ($899/mo billed annually)

Free trial available

No public pricing

No public pricing

Core features
  • BYOK: use your own API keys with 15+ AI providers
  • VS Code extension and JetBrains plugin
  • Agentic coding with planning for complex tasks
  • AI auto-complete for entire lines and blocks of code
  • MCP connections to APIs, docs, and databases
  • Local model support (Ollama, LM Studio)
  • Custom rules and live context tracking
  • Open source with privacy-first architecture
  • Web scraping
  • Data extraction
  • Browser automation
  • AI agents
  • Anti-blocking
  • Proxy rotation
  • Open-source tools (Crawlee)
  • Ready-made tools and code templates
  • Fast tensor operations
  • Differentiable tensors for gradient-based optimization
  • Network connectivity
  • Integration with Bun and Flashlight
  • Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
Use cases
  • AI-assisted coding inside VS Code or JetBrains IDEs
  • Handling complex multi-file coding tasks with agentic mode
  • Code generation, refactoring, and debugging
  • Using preferred cloud or local AI models with full cost control
  • Enterprise AI transformation via AI-First Services (voice and omnichannel agents)
  • Data for generative AI
  • Lead generation
  • Market research
  • Sentiment analysis
  • Creating and manipulating datasets
  • Training small machine learning models
  • Implementing advanced training and inference logic
  • Building applications that require tensor computations
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